Journal of Water Resources Planning and Management

Probabilistic reliability measures for the performance of water distribution networks are developed and analytical methods for their computation explained. The paper begins with a review of reliability considerations and measures for water supply systems, making use of similar notions in other fields. It classifies reliability analyses according to the level of detail with which the water system is modeled, and then concentrates on methods relevant to networks. Two probabilistic measures, reachability (connection of a specific demand node to at least one source) and connectivity, are explored for use in water distribution systems. Two algorithms for their computation are presented, one for series‐parallel networks and one for general networks. These measures are computed for two systems, each with ten nodes. Additionally, the probability that a given point receives sufficient supply is proposed for use as a reliability measure. For the calculation of this measure, an algorithm is provided that combines a capacitated network algorithm with a method to efficiently search through network configurations involving multiple link failures. This measure is calculated for the two sample systems.

Following a companion paper on analytical methods, this paper presents simulation as a complementary method for analyzing the reliability of water distribution networks. For this simulation, the distribution system is modeled as a network whose pipes and pumps are subject to failure. Nodes are targeted to receive a given supply at a given head. If this head is not attainable, supply at the node is reduced. Pumps and pipes fail randomly, according to probability distributions with user‐specified parameters. Several reliability measures are estimated with this simulation. Confidence intervals are also supplied for some of these reliability measures. Simulation results are presented for a small network (ten nodes) and a larger network (sixteen nodes). Simulation enables computation of a much broader class of reliability measures than do analytical methods, but it requires considerably more computer time and its results are less easy to generalize. It is therefore recommended that analytical and simulation methods be used together when assessing the reliability of a system and considering improvements.

Interest is growing in determining the quality variations that exist in drinking water distribution systems. This paper is dedicated to understanding distribution‐system quality issues and to the development of a model that will enhance this understanding. A dynamic algorithm that can be used to predict water quality variations is described in this paper. Determination of the blending of flows from separate sources, tracing of transient concentrations in the system, and establishment of a compliance monitoring system are only a few of the potential uses of such a model. The model has been implemented on a microcomputer and applied to the North Penn Water Authority distribution system, Lansdale, Pennsylvania. It shows good correspondence with observed field data.

An integrated, rainfall‐runoff and runoff‐receiving waterquality modeling protocol was developed to quantify the impact of combined sewer overflow events on in‐stream dissolved oxygen concentration. Modeling assumptions and input data requirements are consistent with intended usage as a planning and management tool. The modeling protocol was successfully calibrated and verified using data collected from several storm events occurring during the summer and fall of 1982. The expected frequency of in‐stream dissolved oxygen violation was determined from the analysis of historical records containing 208 combined sewer overflow events. 42% of these events resulted in minimum dissolved oxygen values below the 4.0 mg/L standard. Sludge deposit resuspension was demonstrated for a monitored high flow event when the in‐stream velocity was computed as 0.689 m/s (2.26 ft/sec).

The economic yield of a flood‐plain zoning program is measured by cost‐benefit analysis. The methodology entails the use of a probabilistic hydroeconomic model to evaluate expected flood damages with and without zoning. The application shows that this type of program, albeit cost‐effective overall, may be unacceptable for various reasons to the various parties involved.

This paper describes a computer‐aided methodology designed to aid in the determination of water quality and ecological change resulting from nonpoint sources of water pollution. The nonpoint monitoring program design conceptual model developed by the writers involves the following steps: (1) The definition of monitoring program objectives to guide data‐collection efforts; (2) a choice of levels of detail to apply in carrying out the various steps of the procedure; (3) a watershed analysis to identify locations of the potentially most critical pollutant loadings; (4) the development of a monitoring program to detect and verify statistically the source or sources of a nonpoint pollution problem; and (5) prioritization of monitoring tasks with reference to trie program objectives. Spreadsheet software with graphics is used to simplify the watershed analysis. FORTRAN programs are applied to facilitate the design of alternative sampling programs and to prioritize the tasks. A case study example on the Stillaguamish River Basin in Washington State is presented to demonstrate an application of the model.

A risk‐based design procedure for hydrograph‐controlled release sewage lagoons is derived. This procedure is based on a stochastic analysis of flood interarrival time, duration, and volume. By modeling streamflow as a Poisson counting process, stochastic sequences consisting of maximum interarrival times and minimum duration are constructed. These sequences are used as the basis for lagoon design by calculating their recurrence intervals based on the joint probability of exceedance of the components of the sequence. Sequences such as those derived here are shown to occur in nature.